ZOMP: Zeroth-Order Multi-Modal Prompt Tuning for Vision-Language Models
ZOMP is a forward-only method to tune deep prompts in vision-language models without needing backpropagation through frozen encoders. It achieves high performance under limited query budgets by combining cross-modal low-rank factorization, gradient-correction momentum, and a budget-indexed rank schedule. This allows it to efficiently explore the search space and find state-of-the-art results.